Information collection, management, and analysis have changed work processes and associated data management. Automation and improvements in work processes have expanded scope of capabilities offered by businesses. With the development of faster and smaller electronics, execution of mass processes at data analysis systems have become feasible. Indeed, analysis work at data centers, data warehouses, data workstations have become common business and private features in modern work and personal environments. Such systems provide a wide variety of applications such as web browsers that present data management tools. Many such applications present large datasets to attempt to improve consumption of big data. Big data gathering and presentation consumes significant resources and performance at a promise of improved processes and condensed task flows.
Data presentation techniques are becoming ever more important as big data grows in popularity across the computer industry. Varieties of techniques are necessary for presenting large data quantities found in big data, to facilitate mining of the relevant insights, and (ultimately) to deliver the benefit of relevant insights to stakeholders. There are currently significant gaps within data presentation methods employed when presenting large datasets and preserving focus in a presented portion of a large dataset. Lack of easy to use data presentation methods lead to underutilization of collected large datasets.